(42) #63 Notre Dame (10-10)

1459.46 (277)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
69 Auburn Loss 8-13 -25.09 76 4.54% Counts Feb 22nd Easterns Qualifier 2025
64 James Madison Loss 11-13 -10.99 70 4.54% Counts Feb 22nd Easterns Qualifier 2025
128 SUNY-Binghamton Win 13-10 -0.15 178 4.54% Counts Feb 22nd Easterns Qualifier 2025
27 South Carolina Loss 6-13 -13.32 50 4.54% Counts (Why) Feb 22nd Easterns Qualifier 2025
49 North Carolina State Loss 14-15 -0.94 21 4.54% Counts Feb 23rd Easterns Qualifier 2025
84 Ohio State Loss 8-15 -33.53 51 4.54% Counts Feb 23rd Easterns Qualifier 2025
87 Temple Loss 13-15 -17.26 179 4.54% Counts Feb 23rd Easterns Qualifier 2025
11 Davenport Loss 6-13 -4.48 377 5.4% Counts (Why) Mar 15th Grand Rapids Invite 2025
143 Michigan Tech Win 14-6 11.62 73 5.4% Counts (Why) Mar 15th Grand Rapids Invite 2025
190 Toronto Win 10-7 -11.32 142 5.11% Counts Mar 15th Grand Rapids Invite 2025
60 Michigan State Loss 11-12 -5.6 88 5.4% Counts Mar 16th Grand Rapids Invite 2025
221 Wisconsin-B Win 13-7 -10.92 102 5.4% Counts (Why) Mar 16th Grand Rapids Invite 2025
123 Wisconsin-Milwaukee Win 11-6 12.61 70 5.11% Counts (Why) Mar 16th Grand Rapids Invite 2025
104 Alabama Win 14-7 23.39 10 6.06% Counts (Why) Mar 29th Huck Finn 2025
44 Emory Win 14-10 35.33 42 6.06% Counts Mar 29th Huck Finn 2025
77 Iowa State Win 15-9 26.21 79 6.06% Counts Mar 29th Huck Finn 2025
194 Saint Louis** Win 15-6 0 10 0% Ignored (Why) Mar 29th Huck Finn 2025
35 Chicago Win 12-8 41.05 97 6.06% Counts Mar 30th Huck Finn 2025
11 Davenport Loss 7-15 -5.07 377 6.06% Counts (Why) Mar 30th Huck Finn 2025
51 Purdue Loss 9-11 -9.86 185 6.06% Counts Mar 30th Huck Finn 2025
**Blowout Eligible. Learn more about how this works here.

FAQ

The results on this page ("USAU") are the results of an implementation of the USA Ultimate Top 20 algorithm, which is used to allocate post season bids to both colleg and club ultimate teams. The data was obtained by scraping USAU's score reporting website. Learn more about the algorithm here. TL;DR, here is the rating function. Every game a team plays gets a rating equal to the opponents rating +/- the score value. With all these data points, we iterate team ratings until convergence. There is also a rule for discounting blowout games (see next FAQ)
For reference, here is handy table with frequent game scrores and the resulting game value:
"...if a team is rated more than 600 points higher than its opponent, and wins with a score that is more than twice the losing score plus one, the game is ignored for ratings purposes. However, this is only done if the winning team has at least N other results that are not being ignored, where N=5."

Translation: if a team plays a game where even earning the max point win would hurt them, they can have the game ignored provided they win by enough and have suffficient unignored results.